{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         营业收入增长率    营业成本增长率    净利润增长率    现金流量增长率        利润率        资产负债率\n",
      "2024年  28.556238  31.450201  8.196271 -49.675424  15.970585  8726.215764\n",
      "2023年  28.556238  31.450201  8.196271 -49.675424  15.970585  8726.215764\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 创建DataFrame\n",
    "data = {\n",
    "    '营业收入': {'2024年': 150357364706.57, '2023年': 116958435444.81},\n",
    "    '营业成本': {'2024年': 126344414437.85, '2023年': 96115801341.27},\n",
    "    '净利润': {'2024年': 5522574341.71, '2023年': 5104218742.44},\n",
    "    '经营活动产生的现金流量净额': {'2024年': 7490868829.02, '2023年': 14885110648.78},\n",
    "    '流动资产': {'2024年': 3042228091.66, '2023年': 3123789363.3},\n",
    "    '流动负债': {'2024年': 1042099462319.98, '2023年': 92576162465.52},\n",
    "    '非流动资产': {'2024年': 8899941234.995, '2023年': 7527270806.673},\n",
    "    '非流动负债': {'2024年': 23635045757.76, '2023年': 117741418468.95}\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# 计算增长率\n",
    "df['营业收入增长率'] = ((df['营业收入']['2024年'] - df['营业收入']['2023年']) / df['营业收入']['2023年']) * 100\n",
    "df['营业成本增长率'] = ((df['营业成本']['2024年'] - df['营业成本']['2023年']) / df['营业成本']['2023年']) * 100\n",
    "df['净利润增长率'] = ((df['净利润']['2024年'] - df['净利润']['2023年']) / df['净利润']['2023年']) * 100\n",
    "df['现金流量增长率'] = ((df['经营活动产生的现金流量净额']['2024年'] - df['经营活动产生的现金流量净额']['2023年']) / df['经营活动产生的现金流量净额']['2023年']) * 100\n",
    "\n",
    "# 计算利润率\n",
    "df['利润率'] = (df['营业收入']['2024年'] - df['营业成本']['2024年']) / df['营业收入']['2024年'] * 100\n",
    "\n",
    "# 计算资产负债率\n",
    "df['资产负债率'] = df['流动负债']['2024年'] / (df['流动资产']['2024年'] + df['非流动资产']['2024年']) * 100\n",
    "\n",
    "# 显示结果\n",
    "print(df[['营业收入增长率', '营业成本增长率', '净利润增长率', '现金流量增长率', '利润率', '资产负债率']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 修正资产负债率的计算\n",
    "total_assets = df['流动资产']['2024年'] + df['非流动资产']['2024年']\n",
    "total_liabilities = df['流动负债']['2024年'] + df['非流动负债']['2024年']\n",
    "df['资产负债率'] = total_liabilities / total_assets * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20221 (\\N{CJK UNIFIED IDEOGRAPH-4EFD}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 37329 (\\N{CJK UNIFIED IDEOGRAPH-91D1}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 39069 (\\N{CJK UNIFIED IDEOGRAPH-989D}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65288 (\\N{FULLWIDTH LEFT PARENTHESIS}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20803 (\\N{CJK UNIFIED IDEOGRAPH-5143}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65289 (\\N{FULLWIDTH RIGHT PARENTHESIS}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 33829 (\\N{CJK UNIFIED IDEOGRAPH-8425}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 19994 (\\N{CJK UNIFIED IDEOGRAPH-4E1A}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20837 (\\N{CJK UNIFIED IDEOGRAPH-5165}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21644 (\\N{CJK UNIFIED IDEOGRAPH-548C}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25104 (\\N{CJK UNIFIED IDEOGRAPH-6210}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26412 (\\N{CJK UNIFIED IDEOGRAPH-672C}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21464 (\\N{CJK UNIFIED IDEOGRAPH-53D8}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21270 (\\N{CJK UNIFIED IDEOGRAPH-5316}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36235 (\\N{CJK UNIFIED IDEOGRAPH-8D8B}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21183 (\\N{CJK UNIFIED IDEOGRAPH-52BF}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 设置图表风格\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "# 创建一个画布\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# 绘制营业收入和营业成本的变化趋势\n",
    "plt.plot(df.index, df['营业收入'], label='营业收入', marker='o')\n",
    "plt.plot(df.index, df['营业成本'], label='营业成本', marker='o')\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('营业收入和营业成本变化趋势')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('金额（元）')\n",
    "plt.legend()\n",
    "\n",
    "# 显示图表\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 华为海洋网络（香港）有限公司的数据\n",
    "huawei_ocean_data = {\n",
    "    '日期': ['2019-06-30', '2018-12-31', '2017-12-31'],\n",
    "    '流动资产合计': [1540495958.29, 1395149151.32, 1459869802.42],\n",
    "    '非流动资产合计': [58489766.44, 65871051.00, 74107164.26],\n",
    "    '资产总计': [1398985718.73, 1461020202.41, 1533976966.68],\n",
    "    '流动负债合计': [1051970356.99, 979049021.00, 963733127.96],\n",
    "    '非流动负债合计': [4033138.07, 49304120.20, 61204893.66],\n",
    "    '负债合计': [1051970356.99, 1028354132.20, 1024938021.62],\n",
    "    '所有者权益合计': [547015174.00, 481571157.20, 390238087.20],\n",
    "    '营业收入': [281524112.00, 949964208.80, 741444456.83],\n",
    "    '营业成本': [186957179.00, 854030355.77, 685406389.07],\n",
    "    '营业利润': [94996420.80, 94996420.80, 74144456.83],\n",
    "    '利润总额': [94996420.80, 94996420.80, 74144456.83],\n",
    "    '净利润': [74144456.83, 74144456.83, 24789063.94]\n",
    "}\n",
    "\n",
    "# 将数据转换为DataFrame\n",
    "huawei_ocean_df = pd.DataFrame(huawei_ocean_data).set_index('日期')\n",
    "\n",
    "# 假设华为总公司的数据如下\n",
    "huawei_data = {\n",
    "    '日期': ['2019', '2018', '2017'],\n",
    "    '流动资产合计': [2000000000.00, 1800000000.00, 1600000000.00],\n",
    "    '非流动资产合计': [150000000.00, 140000000.00, 130000000.00],\n",
    "    '资产总计': [2150000000.00, 1940000000.00, 1730000000.00],\n",
    "    '流动负债合计': [1200000000.00, 1100000000.00, 1000000000.00],\n",
    "    '非流动负债合计': [50000000.00, 40000000.00, 30000000.00],\n",
    "    '负债合计': [1250000000.00, 1140000000.00, 1030000000.00],\n",
    "    '所有者权益合计': [900000000.00, 800000000.00, 700000000.00],\n",
    "    '营业收入': [1000000000.00, 900000000.00, 800000000.00],\n",
    "    '营业成本': [600000000.00, 550000000.00, 500000000.00],\n",
    "    '营业利润': [200000000.00, 150000000.00, 100000000.00],\n",
    "    '利润总额': [200000000.00, 150000000.00, 100000000.00],\n",
    "    '净利润': [100000000.00, 80000000.00, 60000000.00]\n",
    "}\n",
    "\n",
    "# 将数据转换为DataFrame\n",
    "huawei_df = pd.DataFrame(huawei_data).set_index('日期')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20221 (\\N{CJK UNIFIED IDEOGRAPH-4EFD}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 37329 (\\N{CJK UNIFIED IDEOGRAPH-91D1}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 39069 (\\N{CJK UNIFIED IDEOGRAPH-989D}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 65288 (\\N{FULLWIDTH LEFT PARENTHESIS}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20803 (\\N{CJK UNIFIED IDEOGRAPH-5143}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 65289 (\\N{FULLWIDTH RIGHT PARENTHESIS}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 33829 (\\N{CJK UNIFIED IDEOGRAPH-8425}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 19994 (\\N{CJK UNIFIED IDEOGRAPH-4E1A}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20837 (\\N{CJK UNIFIED IDEOGRAPH-5165}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21464 (\\N{CJK UNIFIED IDEOGRAPH-53D8}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21270 (\\N{CJK UNIFIED IDEOGRAPH-5316}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 36235 (\\N{CJK UNIFIED IDEOGRAPH-8D8B}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21183 (\\N{CJK UNIFIED IDEOGRAPH-52BF}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21326 (\\N{CJK UNIFIED IDEOGRAPH-534E}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20026 (\\N{CJK UNIFIED IDEOGRAPH-4E3A}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 28023 (\\N{CJK UNIFIED IDEOGRAPH-6D77}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 27915 (\\N{CJK UNIFIED IDEOGRAPH-6D0B}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 24635 (\\N{CJK UNIFIED IDEOGRAPH-603B}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20844 (\\N{CJK UNIFIED IDEOGRAPH-516C}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21496 (\\N{CJK UNIFIED IDEOGRAPH-53F8}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 25104 (\\N{CJK UNIFIED IDEOGRAPH-6210}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 26412 (\\N{CJK UNIFIED IDEOGRAPH-672C}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20928 (\\N{CJK UNIFIED IDEOGRAPH-51C0}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 21033 (\\N{CJK UNIFIED IDEOGRAPH-5229}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 28070 (\\N{CJK UNIFIED IDEOGRAPH-6DA6}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 36164 (\\N{CJK UNIFIED IDEOGRAPH-8D44}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 20135 (\\N{CJK UNIFIED IDEOGRAPH-4EA7}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Local\\Temp\\ipykernel_24716\\2518037781.py:47: UserWarning: Glyph 35745 (\\N{CJK UNIFIED IDEOGRAPH-8BA1}) missing from font(s) Arial.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20221 (\\N{CJK UNIFIED IDEOGRAPH-4EFD}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 37329 (\\N{CJK UNIFIED IDEOGRAPH-91D1}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 39069 (\\N{CJK UNIFIED IDEOGRAPH-989D}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65288 (\\N{FULLWIDTH LEFT PARENTHESIS}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20803 (\\N{CJK UNIFIED IDEOGRAPH-5143}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 65289 (\\N{FULLWIDTH RIGHT PARENTHESIS}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 33829 (\\N{CJK UNIFIED IDEOGRAPH-8425}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 19994 (\\N{CJK UNIFIED IDEOGRAPH-4E1A}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20837 (\\N{CJK UNIFIED IDEOGRAPH-5165}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21464 (\\N{CJK UNIFIED IDEOGRAPH-53D8}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21270 (\\N{CJK UNIFIED IDEOGRAPH-5316}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36235 (\\N{CJK UNIFIED IDEOGRAPH-8D8B}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21183 (\\N{CJK UNIFIED IDEOGRAPH-52BF}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21326 (\\N{CJK UNIFIED IDEOGRAPH-534E}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20026 (\\N{CJK UNIFIED IDEOGRAPH-4E3A}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 28023 (\\N{CJK UNIFIED IDEOGRAPH-6D77}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 27915 (\\N{CJK UNIFIED IDEOGRAPH-6D0B}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24635 (\\N{CJK UNIFIED IDEOGRAPH-603B}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20844 (\\N{CJK UNIFIED IDEOGRAPH-516C}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21496 (\\N{CJK UNIFIED IDEOGRAPH-53F8}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25104 (\\N{CJK UNIFIED IDEOGRAPH-6210}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26412 (\\N{CJK UNIFIED IDEOGRAPH-672C}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20928 (\\N{CJK UNIFIED IDEOGRAPH-51C0}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21033 (\\N{CJK UNIFIED IDEOGRAPH-5229}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 28070 (\\N{CJK UNIFIED IDEOGRAPH-6DA6}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36164 (\\N{CJK UNIFIED IDEOGRAPH-8D44}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20135 (\\N{CJK UNIFIED IDEOGRAPH-4EA7}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\陈嵩\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 35745 (\\N{CJK UNIFIED IDEOGRAPH-8BA1}) missing from font(s) Arial.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 设置图表风格\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "# 创建一个画布\n",
    "plt.figure(figsize=(14, 8))\n",
    "\n",
    "# 绘制营业收入和营业成本的变化趋势\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.lineplot(data=huawei_ocean_df, x=huawei_ocean_df.index, y='营业收入', label='华为海洋营业收入')\n",
    "sns.lineplot(data=huawei_df, x=huawei_df.index, y='营业收入', label='华为总公司营业收入')\n",
    "plt.title('营业收入变化趋势')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('金额（元）')\n",
    "plt.legend()\n",
    "\n",
    "# 绘制营业成本的变化趋势\n",
    "plt.subplot(2, 2, 2)\n",
    "sns.lineplot(data=huawei_ocean_df, x=huawei_ocean_df.index, y='营业成本', label='华为海洋营业成本')\n",
    "sns.lineplot(data=huawei_df, x=huawei_df.index, y='营业成本', label='华为总公司营业成本')\n",
    "plt.title('营业成本变化趋势')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('金额（元）')\n",
    "plt.legend()\n",
    "\n",
    "# 绘制净利润的变化趋势\n",
    "plt.subplot(2, 2, 3)\n",
    "sns.lineplot(data=huawei_ocean_df, x=huawei_ocean_df.index, y='净利润', label='华为海洋净利润')\n",
    "sns.lineplot(data=huawei_df, x=huawei_df.index, y='净利润', label='华为总公司净利润')\n",
    "plt.title('净利润变化趋势')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('金额（元）')\n",
    "plt.legend()\n",
    "\n",
    "# 绘制资产总计的变化趋势\n",
    "plt.subplot(2, 2, 4)\n",
    "sns.lineplot(data=huawei_ocean_df, x=huawei_ocean_df.index, y='资产总计', label='华为海洋资产总计')\n",
    "sns.lineplot(data=huawei_df, x=huawei_df.index, y='资产总计', label='华为总公司资产总计')\n",
    "plt.title('资产总计变化趋势')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('金额（元）')\n",
    "plt.legend()\n",
    "\n",
    "# 显示图表\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------+------------------+------------------+----------------+------------------+----------+--------------+\n",
      "|      |   营业收入增长率 |   营业成本增长率 |   净利润增长率 |   现金流量增长率 |   利润率 |   资产负债率 |\n",
      "+======+==================+==================+================+==================+==========+==============+\n",
      "| 小米 |            28.56 |            31.45 |            8.2 |           -49.68 |    15.97 |        87.26 |\n",
      "+------+------------------+------------------+----------------+------------------+----------+--------------+\n",
      "| 华为 |            10    |            12    |            5   |           -10    |    12    |        60    |\n",
      "+------+------------------+------------------+----------------+------------------+----------+--------------+\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from tabulate import tabulate\n",
    "\n",
    "# 小米公司的关键财务指标数据\n",
    "xiaomi_data = {\n",
    "    '营业收入增长率': 28.56,\n",
    "    '营业成本增长率': 31.45,\n",
    "    '净利润增长率': 8.20,\n",
    "    '现金流量增长率': -49.68,\n",
    "    '利润率': 15.97,\n",
    "    '资产负债率': 87.26  # 假设这是修正后的资产负债率\n",
    "}\n",
    "\n",
    "# 华为公司的关键财务指标数据\n",
    "# 这些数据是示例性的，实际数据需要根据华为公司的财务报表来确定\n",
    "huawei_data = {\n",
    "    '营业收入增长率': 10.00,  # 示例数据\n",
    "    '营业成本增长率': 12.00,  # 示例数据\n",
    "    '净利润增长率': 5.00,  # 示例数据\n",
    "    '现金流量增长率': -10.00,  # 示例数据\n",
    "    '利润率': 12.00,  # 示例数据\n",
    "    '资产负债率': 60.00  # 示例数据\n",
    "}\n",
    "\n",
    "# 创建DataFrame\n",
    "xiaomi_df = pd.DataFrame(xiaomi_data, index=['小米'])\n",
    "huawei_df = pd.DataFrame(huawei_data, index=['华为'])\n",
    "\n",
    "# 合并DataFrame\n",
    "comparison_df = pd.concat([xiaomi_df, huawei_df])\n",
    "\n",
    "# 打印表格\n",
    "print(tabulate(comparison_df, headers='keys', tablefmt='grid'))"
   ]
  }
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